I'm a Software Engineer specializing in Infrastructure and Cloud Engineering at SITA, with a solid foundation in Artificial Intelligence and Full Stack Development. Passionate about creating innovative solutions, I have contributed to a range of projects spanning AI/ML systems, cloud infrastructure, and DevOps. My experience enables me to design scalable systems, optimize cloud workflows, and develop intelligent software solutions that solve real-world challenges. 🚀
- Containerized Machine Learning Model Deployment: Built a scalable ML model deployment pipeline using Docker and Kubernetes. This project showcases the orchestration of a machine learning model in a cloud environment, allowing for seamless integration and containerization. View Repository
- Cloud Automation with Terraform and Python Automation Scripts: Developed an automated infrastructure management system using Terraform for provisioning and Python for automating configuration and deployment tasks. The project provisions and configures cloud infrastructure on Azure, demonstrating my expertise in infrastructure-as-code (IaC) and custom automation scripts to streamline cloud operations. View Repository
- Social Media Sentiment Analysis Tool: A tool that leverages NLP to analyze sentiments on social media platforms, providing real-time insights into public opinion. View Repository
- Fraud Detection in Financial Transactions: Designed and implemented a machine learning system for detecting fraudulent financial transactions using anomaly detection and feature importance techniques. View Repository
- CI/CD Pipeline for Cloud-Based Applications: Created a fully automated CI/CD pipeline using GitHub Actions and Azure Pipelines, enabling continuous integration, testing, and deployment of cloud-based applications with monitoring and logging features. View Repository
- Antibiotic Discovery Using Generative AI: Applied generative AI techniques to explore potential antibiotic compounds, contributing to advancements in drug discovery using machine learning. View Repository
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Languages:
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Proficient in building web applications using JavaScript and TypeScript for both client-side and server-side development, ensuring type safety and scalable codebases.
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Expertise in Python for backend development, automation, and scripting tasks, with a focus on frameworks like Flask and Django for web services.
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Experience in developing backend systems using Java, with a focus on object-oriented programming and enterprise-grade applications.
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Strong understanding of Rust for systems programming and backend services, with a focus on performance, safety, and concurrency.
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Front-End:
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Proficient in building interactive, single-page applications (SPAs) using React.js, leveraging component-based architecture for maintainable and scalable front-end solutions.
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Solid foundation in HTML5 and CSS3 for creating responsive and accessible user interfaces.
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Utilized for rapid UI development, ensuring responsiveness and consistency across various devices and screen sizes.
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Back-End:
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Used to build scalable server-side applications, leveraging asynchronous I/O and event-driven architecture for handling high-throughput scenarios.
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Built RESTful APIs and web services using Express.js for lightweight and efficient back-end solutions.
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Built RESTful APIs and web services using Express.js for lightweight and efficient back-end solutions.
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Experience with relational databases (e.g., MySQL, PostgreSQL) and document-based NoSQL databases (e.g., MongoDB), focusing on data modeling, query optimization, and efficient data storage solutions.
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Cloud Engineering:
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Skilled in managing cloud resources with Azure, including virtual machines, databases, and Azure Kubernetes Service (AKS), while utilizing Azure Pipelines for continuous integration and deployment (CI/CD).
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Experience with AWS services for building scalable cloud applications, including EC2, S3, RDS, and Lambda functions.
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Expertise in orchestrating containerized applications with Kubernetes, ensuring high availability, scalability, and automated deployment strategies using AKS or GKE.
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Proficient in using Terraform for Infrastructure-as-Code (IaC), automating cloud resource provisioning, and managing multi-cloud environments.
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Utilized Docker for containerization, enabling consistent environments across development and production, and simplifying application deployment with Docker Compose.
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CI/CD & DevOps:
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Set up automated workflows using GitHub Actions for continuous integration and deployment, with a focus on testing, security, and automated deployment pipelines.
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Managed complex deployment pipelines for Azure-based services, integrating testing, containerization, and monitoring throughout the development lifecycle.
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Version Control:
- Deployment:
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- Data Handling:
- Machine Learning: Supervised and Unsupervised Learning, Decision Trees, SVM, XGBoost, Random Forest, CatBoost.
- Deep Learning: CNNs, RNNs, GANs, Transfer Learning.
- Natural Language Processing: Sentiment Analysis, Language Generation, Text Classification.
- Reinforcement Learning: Q-Learning, Policy Gradient Methods.
- Explainable AI & Active Learning: Techniques for model interpretability and continuous feedback-driven improvements.
- MLOps & Data Engineering: Model Deployment, Data Pipelines, ETL, Big Data Technologies, and Cloud Infrastructure (using Kubernetes, Docker, and Terraform).
Currently contributing to cutting-edge cloud engineering projects at SITA, I aim to drive impactful initiatives in cloud infrastructure, automation, and AI-based solutions. I'm always looking for opportunities to collaborate on innovative projects and enhance my expertise in AI and Cloud Engineering.
I’d love to discuss technology, AI, cloud infrastructure, or any exciting collaboration opportunities!
🌱 Currently expanding my knowledge in advanced cloud computing techniques and AI optimization.
⚡ Fun fact: I enjoy participating in hackathons and solving algorithmic challenges.